There appear to be significant redundancies within G-8 Tech positions, particularly across product owner, GCL, and architect roles, signaling imminent consolidation in this area. Concurrently, there is a renewed focus on tech team productivity, placing large AI teams under intense scrutiny. The prevailing sentiment suggests that data scientists are primarily producing low-value papers with virtually no impact on actual business deliverables.
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In the contemporary landscape of Large Language Models (LLMs) and proliferating open-source options, many specialized AI teams function primarily as AI model integrators rather than core creators. Their operational scope is frequently limited to downloading pre-existing open-source models, executing minimal or sometimes unnecessary fine-tuning, and deploying these assets into production. Alternatively, they rely heavily on established agentic frameworks to orchestrate API calls to external LLMs and construct basic operational workflows. Consequently, standard software engineering and technology teams are often better equipped to manage, optimize, and scale these integration tasks more efficiently.
I believe it because they ended up scaling back on AI training. This place is too conservative to be using AI, especially with the negative press on AI recently